Last Time: Acting Humanly: The Full Turing TestLast time: The Turing TestSlide 3Slide 4Slide 5Slide 6This time: OutlineWhat is an (Intelligent) Agent?Slide 9Intelligent Agents and Artificial IntelligenceAgent TypesRational AgentsRemember: the Beobot exampleA Windshield Wiper AgentA Windshield Wiper Agent (Cont’d)Towards Autonomous VehiclesInteracting AgentsSlide 18Conflict Resolution by Action Selection AgentsThe Right Thing = The Rational ActionSlide 21Behavior and performance of IAsLook up tableClosed formHow is an Agent different from other software?Slide 26Environment TypesSlide 28Slide 29Environment typesSlide 31Slide 32Slide 33Slide 34Structure of Intelligent AgentsUsing a look-up-table to encode f : P*  ASlide 37Agent typesSlide 39Slide 40Reflex agentsReactive agentsReflex agents w/ stateGoal-based agentsUtility-based agentsMobile agentsSlide 47Slide 48Slide 49Information agentsSummaryCS 460, Lecture 2Last Time: Acting Humanly: The Full Turing Test•Alan Turing's 1950 article Computing Machinery and Intelligence discussed conditions for considering a machine to be intelligent•“Can machines think?”  “Can machines behave intelligently?”•The Turing test (The Imitation Game): Operational definition of intelligence.•Computer needs to possess: Natural language processing, Knowledge representation, Automated reasoning, and Machine learning•Problem: 1) Turing test is not reproducible, constructive, and amenable to mathematic analysis. 2) What about physical interaction with interrogator and environment?•Total Turing Test: Requires physical interaction and needs perception and actuation.CS 460, Lecture 2Last time: The Turing Testhttp://www.ai.mit.edu/projects/infolab/http://aimovie.warnerbros.comCS 460, Lecture 2Last time: The Turing Testhttp://www.ai.mit.edu/projects/infolab/http://aimovie.warnerbros.comCS 460, Lecture 2Last time: The Turing Testhttp://www.ai.mit.edu/projects/infolab/http://aimovie.warnerbros.comCS 460, Lecture 2Last time: The Turing Testhttp://www.ai.mit.edu/projects/infolab/http://aimovie.warnerbros.comCS 460, Lecture 2Last time: The Turing Testhttp://www.ai.mit.edu/projects/infolab/http://aimovie.warnerbros.comCS 460, Lecture 2This time: Outline•Intelligent Agents (IA)•Environment types•IA Behavior•IA Structure•IA TypesCS 460, Lecture 2What is an (Intelligent) Agent?•An over-used, over-loaded, and misused term.•Anything that can be viewed as perceiving its environment through sensors and acting upon that environment through its effectors to maximize progress towards its goals.CS 460, Lecture 2What is an (Intelligent) Agent?•PAGE (Percepts, Actions, Goals, Environment)•Task-specific & specialized: well-defined goals and environment•The notion of an agent is meant to be a tool for analyzing systems, •It is not a different hardware or new programming languagesCS 460, Lecture 2•Example: Human mind as network of thousands or millions of agents working in parallel. To produce real artificial intelligence, this school holds, we should build computer systems that also contain many agents and systems for arbitrating among the agents' competing results. •Distributed decision-making and control•Challenges:•Action selection: What next actionto choose•Conflict resolutionIntelligent Agents and Artificial IntelligencesensorseffectorsAgencyCS 460, Lecture 2Agent TypesWe can split agent research into two main strands:•Distributed Artificial Intelligence (DAI) – Multi-Agent Systems (MAS) (1980 – 1990)•Much broader notion of "agent" (1990’s – present)•interface, reactive, mobile, informationCS 460, Lecture 2Rational AgentsEnvironmentAgentperceptsactions?SensorsEffectorsHow to design this?CS 460, Lecture 2Remember: the Beobot exampleCS 460, Lecture 2A Windshield Wiper AgentHow do we design a agent that can wipe the windshields when needed?•Goals? •Percepts?•Sensors?•Effectors?•Actions?•Environment?CS 460, Lecture 2A Windshield Wiper Agent (Cont’d)•Goals: Keep windshields clean & maintain visibility•Percepts: Raining, Dirty•Sensors: Camera (moist sensor)•Effectors: Wipers (left, right, back)•Actions: Off, Slow, Medium, Fast•Environment: Inner city, freeways, highways, weather …CS 460, Lecture 2Towards Autonomous Vehicleshttp://iLab.usc.edu http://beobots.orgCS 460, Lecture 2Interacting AgentsCollision Avoidance Agent (CAA)•Goals: Avoid running into obstacles•Percepts ?•Sensors?•Effectors ?•Actions ?•Environment: FreewayLane Keeping Agent (LKA)•Goals: Stay in current lane•Percepts ?•Sensors?•Effectors ?•Actions ?•Environment: FreewayCS 460, Lecture 2Interacting AgentsCollision Avoidance Agent (CAA)•Goals: Avoid running into obstacles•Percepts: Obstacle distance, velocity, trajectory•Sensors: Vision, proximity sensing•Effectors: Steering Wheel, Accelerator, Brakes, Horn, Headlights•Actions: Steer, speed up, brake, blow horn, signal (headlights)•Environment: Freeway Lane Keeping Agent (LKA)•Goals: Stay in current lane•Percepts: Lane center, lane boundaries•Sensors: Vision•Effectors: Steering Wheel, Accelerator, Brakes•Actions: Steer, speed up, brake•Environment: FreewayCS 460, Lecture 2Conflict Resolution by Action Selection Agents•Override: CAA overrides LKA•Arbitrate: if Obstacle is Close then CAAelse LKA•Compromise: Choose action that satisfies bothagents•Any combination of the above•Challenges: Doing the right thingCS 460, Lecture 2The Right Thing = The Rational Action•Rational Action: The action that maximizes the expected value of the performance measure given the percept sequence to date•Rational = Best ?•Rational = Optimal ?•Rational = Omniscience ? •Rational = Clairvoyant ?•Rational = Successful ?CS 460, Lecture 2The Right Thing = The Rational Action•Rational Action: The action that maximizes the expected value of the performance measure given the percept sequence to date•Rational = Best Yes, to the best of its knowledge•Rational = Optimal Yes, to the best of its abilities (incl.•Rational  Omniscience its constraints)•Rational  Clairvoyant •Rational  SuccessfulCS 460, Lecture 2Behavior and performance of IAs•Perception (sequence) to Action Mapping: f : P*  A•Ideal mapping: specifies which actions an agent ought to take at any point in time•Description: Look-Up-Table, Closed Form, etc.